iCushion: A Pressure Map Algorithm for High Accuracy Human Identification
Haojun Ai, Liezhuo Zhang, Zhiyu Yuan, Haitao Huang · 2018
Intelligent Cushion (iCushion) technology is recently booming with embedded pressure array sensors to enable individual-specific sitting experiences. iCushion has the build-in functionality to identify users throughout its use in a continuous and non-intrusive manner. Due to the variability in sitting posture and the angle of seated deflection, the accuracy of user identification remains unstable or unclear with existing solutions. Aiming at this problem, this study develops a two-stage pressure map algorithm based on robust spatial-temporal features. First, pressure maps are collected constantly without limiting the user's posture, based on which an accumulated identity library is established for sitting postures by extracting features from pressure maps. To be specifically, we create a decision tree to classify maps by distances between both ischia and then variances in both areas around ischia in maps are analyzed. Second, the similarity between both maps are measured by the Euclidean distance between feature vectors around ischia for matching maps data. A k-NN voting mechanism is developed to achieve reliability of identification. The resulted iCushion prototype has successfully identified 92.2% of maps with three randomly chosen individuals through four-hour non-stop testing. It holds potentials of non-intrusive and reliable activity recognition in other pervasive applications.